System and method for location insensitive reporting of fractional flow reserve-computed tomography for a given stenosis

1. A computer-implemented method for location insensitive reporting of a fraction flow reserve (FFR) value for a given stenosis, comprising:

obtaining, at a processor, vascular image data from a subject;

identifying, via the processor, a stenosed region within a vessel in the vascular image data;

generating, via the processor, a revascularized model of the vessel based on the vascular image data, wherein in the revascularized model a lumen boundary in the stenosed region is adjusted to have a same cross-sectional area as healthy sections of the vessel both proximal and distal to the stenosed region;

determining, via the processor, a first pressure distribution for the revascularized model at hyperemic flow;

determining, via the processor, a second pressure distribution for the vessel in the vascular image data;

calculating, via the processor, a subtracted pressure distribution by subtracting the second pressure distribution from the first pressure distribution;

determining, via the processor, an asymptotic value for the subtracted pressure distribution;

calculating, via the processor, a value by subtracting the asymptotic value from a pressure value obtained from the second pressure distribution at a location at a beginning of the stenosed region in the vessel; and

normalizing, via the processor, the value to obtain a location independent FFR value for the stenosed region.

2. The computer-implemented method of claim 1 , wherein the location independent FFR value is displayed without a user having to select an actual reporting location for the stenosed region.

3. The computer-implemented method of claim 1 , wherein normalizing the value to obtain the location independent FFR value comprises normalizing the value by an aortic pressure obtained from the subject.

4. The computer-implemented method of claim 1 , wherein the vascular image data is computed tomography angiography image data.

5. The computer-implemented method of claim 1 , further comprising estimating, via the processor, the hyperemic flow based on computed tomography angiography scan data.

6. The computer-implemented method of claim 1 , further comprising determining, via the processor, locations for the beginning and an end of the stenosed region during identification of the stenosed region.

7. The computer-implemented method of claim 1 , wherein determining the first pressure distribution and the second pressure distribution comprises utilizing steady state computational fluid dynamics (CFD) calculations.

8. The computer-implemented method of claim 1 , wherein determining the first pressure distribution and the second pressure distribution comprises using a deep-learning algorithm trained to predict a pressure drop.

9. The computer-implemented method of claim 1 , further comprising generating and displaying, via the processor, an FFR image, wherein the stenosed region in the vessel is identified and the location independent FFR value is displayed.

10. A system for location insensitive reporting of a fraction flow reserve (FFR) value for a given stenosis, comprising:

a memory encoding processor-executable routines; and

a processor configured to access the memory and to execute the processor-executable routines, wherein the processor-executable routines, when executed by the processor, cause the processor to:

obtaining vascular image data from a subject;

identify a stenosed region within a vessel in the vascular image data;

generate a revascularized model of the vessel based on the vascular image data, wherein in the revascularized model a lumen boundary in the stenosed region is adjusted to have a same cross-sectional area as healthy sections of the vessel both proximal and distal to the stenosed region;

determine a first pressure distribution for the revascularized model at hyperemic flow;

determine a second pressure distribution for the vessel in the vascular image data;

calculate a subtracted pressure distribution by subtracting the second pressure distribution from the first pressure distribution;

determine an asymptotic value for the subtracted pressure distribution;

calculate a value by subtracting the asymptotic value from a pressure value obtained from the second pressure distribution at a location at a beginning of the stenosed region in the vessel; and

normalize the value to obtain a location independent FFR value for the stenosed region.

11. The system of claim 10 , wherein normalizing the value to obtain the location independent FFR value comprises normalizing the value by an aortic pressure obtained from the subject.

12. The system of claim 10 , wherein the vascular image data is computed tomography angiography image data.

13. The system of claim 10 , wherein the processor-executable routines, when executed by the processor, cause the processor to estimate the hyperemic flow based on computed tomography angiography scan data.

14. The system of claim 10 , wherein the processor-executable routines, when executed by the processor, cause the processor to determine locations for the beginning and an end of the stenosed region during identification of the stenosed region.

15. The system of claim 10 , wherein determining the first pressure distribution and the second pressure distribution comprises utilizing steady state computational fluid dynamics (CFD) calculations.

16. The system of claim 10 , wherein determining the first pressure distribution and the second pressure distribution comprises using a deep-learning algorithm trained to predict a pressure drop.

17. The system of claim 10 , wherein the processor-executable routines, when executed by the processor, cause the processor to generate and display an FFR image, wherein the stenosed region in the vessel is identified and the location independent FFR value is displayed.

18. The system of claim 10 , wherein the location independent FFR value is displayed without a user having to select an actual reporting location for the stenosed region.

19. A non-transitory computer-readable medium, the computer-readable medium comprising processor-executable code that when executed by a processor, causes the processor to:

obtain vascular image data from a subject;

identify a stenosed region within a vessel in the vascular image data;

generate a revascularized model of the vessel based on the vascular image data, wherein in the revascularized model a lumen boundary in the stenosed region is adjusted to have a same cross-sectional area as healthy sections of the vessel both proximal and distal to the stenosed region;

determine a first pressure distribution for the revascularized model at hyperemic flow;

determine a second pressure distribution for the vessel in the vascular image data;

calculate a subtracted pressure distribution by subtracting the second pressure distribution from the first pressure distribution;

determine an asymptotic value for the subtracted pressure distribution;

calculate a value by subtracting the asymptotic value from a pressure value obtained from the second pressure distribution at a location at a beginning of the stenosed region in the vessel; and

normalize the value to obtain a location independent FFR value for the stenosed region.

20. The non-transitory computer-readable medium of claim 19 , wherein the processor-executable code, when executed by the processor, cause the processor to generate and display an FFR image, wherein the stenosed region in the vessel is identified and the location independent FFR value is displayed, and wherein the location independent FFR value is displayed without a user having select an actual reporting location for the stenosed region.